{"schemaVersion":"jobsearcher.job.v1","id":"969a3a68c1697b4095ea1faa","url":"https://jobsearcher.com/jobs/969a3a68c1697b4095ea1faa","canonicalUrl":"https://jobsearcher.com/jobs/969a3a68c1697b4095ea1faa","title":"Devops Engineer","description":"We are seeking an experienced DevOps Engineer to support a high-impact, multi-workstream AI program focused on enabling the rapid, reliable, and secure delivery of AI/ML applications and services. This role is 100% dedicated to AI initiatives, covering the full lifecycle from early experimentation through full production deployment.\nThe DevOps Engineer will be responsible for building and operating CI/CD pipelines, cloud infrastructure, and runtime platforms that support data-intensive and model-driven workloads. Working closely with Product Teams, Data Engineers, and Data Scientists, this role plays a critical part in streamlining the AI model lifecycle while ensuring enterprise-grade reliability, scalability, security, and governance.\nThis is an excellent opportunity for a DevOps professional interested in working at the intersection of cloud engineering, automation, and AI delivery.\n\nRequisitos:\n\nKey Responsibilities\nPlatform & CI/CD Pipelines\nDesign, implement, and maintain CI/CD pipelines for applications, APIs, batch jobs, platforms, and data pipelines.\nAutomate model build, testing, packaging, versioning, and deployment across development, test, and production environments.\nEstablish standardized and repeatable deployment patterns to support rapid iteration and reliable environment promotion.\nCloud & Infrastructure\nProvision and manage cloud infrastructure (compute, networking, storage) optimized for AI workloads, including batch, containerized, and serverless runtimes.\nImplement Infrastructure as Code (IaC) using Terraform (primary) and/or Bicep.\nDesign and support environment promotion strategies aligned with enterprise architecture standards.\nContainers & Orchestration\nBuild, deploy, and optimize containerized services using Docker.\nOperate workloads on managed container platforms such as OpenShift and AKS.\nImplement autoscaling, resiliency, and operational hardening best practices.\nObservability & Reliability\nEstablish and maintain monitoring, logging, and tracing across applications, AI models, and data pipelines.\nProactively troubleshoot platform, pipeline, and runtime issues using tools such as Datadog, Azure Monitor, and Application Insights.\nEnsure high availability, performance, and operational stability of AI services.\nSecurity, Compliance & Governance\nEmbed security controls into CI/CD pipelines, including automated code scanning, vulnerability detection, secrets management, and CodeQL analysis.\nImplement RBAC, identity management, and data protection aligned with enterprise security and compliance requirements.\nEnsure auditability across source code, pipelines, and runtime environments.\nCollaboration & Enablement\nPartner closely with Data Scientists and ML Engineers to streamline the AI/ML lifecycle from experimentation to production.\nCreate and maintain documentation, runbooks, reusable templates, and reference architectures.\nPromote DevOps and platform best practices across teams.\n\nRequired Qualifications\n3–5+ years of experience in DevOps or Platform Engineering, including production support.\nStrong experience with Windows Server administration and troubleshooting (Linux experience is a plus).\nHands-on expertise with CI/CD tools such as Azure DevOps, GitHub Actions, and Ansible.\nSolid experience with cloud platforms (Azure and AWS), including networking, identity, and storage.\nDeep proficiency with Infrastructure as Code, with Terraform as the primary tool.\nStrong scripting and automation skills (PowerShell required; Python is a plus).\nHands-on experience with Docker and Kubernetes, including deployments, scaling, upgrades, and operational hardening.\nExperience implementing monitoring and observability solutions (e.g., Datadog, Azure Monitor, Application Insights).\nStrong understanding of cost governance, resource design, and platform architecture best practices.\nProven experience implementing security best practices across pipelines and runtime environments (e.g., RBAC, secrets, artifact repositories).\nExcellent communication skills with the ability to collaborate across product, data, security, and architecture teams.\n\nPreferred Qualifications\nExperience operating AI/ML workloads, including:Model packaging and artifact registries\nModel versioning\nControlled and staged rollouts\nFamiliarity with ML platforms and toolchains (e.g., MLflow, Azure ML, or equivalent).\nUnderstanding of data engineering concepts, including batch and streaming pipelines, data quality, schemas, and version management.\nExperience with GPU-aware deployments and cost/performance optimization for training and inference workloads.\nExperience working in large enterprise or highly regulated environments.\n\nWays of Working\nCore collaboration hours aligned with Houston / Central Time preferred.\nOperate within Agile methodologies (Scrum, sprint planning, daily stand-ups).\nParticipate in daily and weekly ceremonies and be available during critical delivery windows.\nEmbrace a culture of transparency, accountability, and continuous improvement.\n\nSuccess Measures\nReduced lead time for changes and faster, more reliable model-to-production cycles.\nHigh service availability, scalability, and performance.\nStrong security posture and auditability across platforms, pipelines, and runtime environments.\nPositive feedback from Architecture, Data Science, Product, and Security stakeholders.\n\nTop 3 Skills for Success\nCI/CD Tooling\nInfrastructure as Code (Terraform – primary)\nCloud Platforms (Azure & AWS)","company":"Insight It Pty","rawCompany":"insight it pty","city":"Big Spring","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-04-14T11:25:19.997Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1244.00","title":"Network and Computer Systems Administrators","slug":"network-and-computer-systems-administrators"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Devops Engineer","description":"We are seeking an experienced DevOps Engineer to support a high-impact, multi-workstream AI program focused on enabling the rapid, reliable, and secure delivery of AI/ML applications and services. This role is 100% dedicated to AI initiatives, covering the full lifecycle from early experimentation through full production deployment.\nThe DevOps Engineer will be responsible for building and operating CI/CD pipelines, cloud infrastructure, and runtime platforms that support data-intensive and model-driven workloads. Working closely with Product Teams, Data Engineers, and Data Scientists, this role plays a critical part in streamlining the AI model lifecycle while ensuring enterprise-grade reliability, scalability, security, and governance.\nThis is an excellent opportunity for a DevOps professional interested in working at the intersection of cloud engineering, automation, and AI delivery.\n\nRequisitos:\n\nKey Responsibilities\nPlatform & CI/CD Pipelines\nDesign, implement, and maintain CI/CD pipelines for applications, APIs, batch jobs, platforms, and data pipelines.\nAutomate model build, testing, packaging, versioning, and deployment across development, test, and production environments.\nEstablish standardized and repeatable deployment patterns to support rapid iteration and reliable environment promotion.\nCloud & Infrastructure\nProvision and manage cloud infrastructure (compute, networking, storage) optimized for AI workloads, including batch, containerized, and serverless runtimes.\nImplement Infrastructure as Code (IaC) using Terraform (primary) and/or Bicep.\nDesign and support environment promotion strategies aligned with enterprise architecture standards.\nContainers & Orchestration\nBuild, deploy, and optimize containerized services using Docker.\nOperate workloads on managed container platforms such as OpenShift and AKS.\nImplement autoscaling, resiliency, and operational hardening best practices.\nObservability & Reliability\nEstablish and maintain monitoring, logging, and tracing across applications, AI models, and data pipelines.\nProactively troubleshoot platform, pipeline, and runtime issues using tools such as Datadog, Azure Monitor, and Application Insights.\nEnsure high availability, performance, and operational stability of AI services.\nSecurity, Compliance & Governance\nEmbed security controls into CI/CD pipelines, including automated code scanning, vulnerability detection, secrets management, and CodeQL analysis.\nImplement RBAC, identity management, and data protection aligned with enterprise security and compliance requirements.\nEnsure auditability across source code, pipelines, and runtime environments.\nCollaboration & Enablement\nPartner closely with Data Scientists and ML Engineers to streamline the AI/ML lifecycle from experimentation to production.\nCreate and maintain documentation, runbooks, reusable templates, and reference architectures.\nPromote DevOps and platform best practices across teams.\n\nRequired Qualifications\n3–5+ years of experience in DevOps or Platform Engineering, including production support.\nStrong experience with Windows Server administration and troubleshooting (Linux experience is a plus).\nHands-on expertise with CI/CD tools such as Azure DevOps, GitHub Actions, and Ansible.\nSolid experience with cloud platforms (Azure and AWS), including networking, identity, and storage.\nDeep proficiency with Infrastructure as Code, with Terraform as the primary tool.\nStrong scripting and automation skills (PowerShell required; Python is a plus).\nHands-on experience with Docker and Kubernetes, including deployments, scaling, upgrades, and operational hardening.\nExperience implementing monitoring and observability solutions (e.g., Datadog, Azure Monitor, Application Insights).\nStrong understanding of cost governance, resource design, and platform architecture best practices.\nProven experience implementing security best practices across pipelines and runtime environments (e.g., RBAC, secrets, artifact repositories).\nExcellent communication skills with the ability to collaborate across product, data, security, and architecture teams.\n\nPreferred Qualifications\nExperience operating AI/ML workloads, including:Model packaging and artifact registries\nModel versioning\nControlled and staged rollouts\nFamiliarity with ML platforms and toolchains (e.g., MLflow, Azure ML, or equivalent).\nUnderstanding of data engineering concepts, including batch and streaming pipelines, data quality, schemas, and version management.\nExperience with GPU-aware deployments and cost/performance optimization for training and inference workloads.\nExperience working in large enterprise or highly regulated environments.\n\nWays of Working\nCore collaboration hours aligned with Houston / Central Time preferred.\nOperate within Agile methodologies (Scrum, sprint planning, daily stand-ups).\nParticipate in daily and weekly ceremonies and be available during critical delivery windows.\nEmbrace a culture of transparency, accountability, and continuous improvement.\n\nSuccess Measures\nReduced lead time for changes and faster, more reliable model-to-production cycles.\nHigh service availability, scalability, and performance.\nStrong security posture and auditability across platforms, pipelines, and runtime environments.\nPositive feedback from Architecture, Data Science, Product, and Security stakeholders.\n\nTop 3 Skills for Success\nCI/CD Tooling\nInfrastructure as Code (Terraform – primary)\nCloud Platforms (Azure & AWS)","datePosted":"2026-04-14T11:25:19.997Z","dateModified":"2026-04-14T11:25:19.997Z","hiringOrganization":{"@type":"Organization","name":"Insight It Pty","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Big Spring","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"969a3a68c1697b4095ea1faa"},"url":"https://jobsearcher.com/jobs/969a3a68c1697b4095ea1faa"}}